temporary and net sinks of atmospheric co due to chemical … · 2020. 7. 31. · chemical...

Biogeosciences, 17, 3875–3890, 2020https://doi.org/10.5194/bg-17-3875-2020© Author(s) 2020. This work is distributed underthe Creative Commons Attribution 4.0 License.

Temporary and net sinks of atmospheric CO2 due to chemicalweathering in subtropical catchment with mixingcarbonate and silicate lithologyYingjie Cao1,3,4, Yingxue Xuan1,2, Changyuan Tang1,2,3, Shuai Guan5, and Yisheng Peng1,31School of Environmental Science and Engineering, Sun Yat-Sen University, Guangzhou, China2School of Geography and Planning, Sun Yat-Sen University, Guangzhou, China3Guangdong Provincial Key Laboratory of Environmental Pollution Control and Remediation Technology,Sun Yat-Sen University, Guangzhou, China4Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai, China5Guangdong Research Institute of Water Resource and Hydropower, Guangzhou, China

Correspondence: Changyuan Tang ([email protected], [email protected])

Received: 7 August 2019 – Discussion started: 13 November 2019Revised: 21 May 2020 – Accepted: 13 June 2020 – Published: 31 July 2020

Abstract. The study provided the major ion chemistry,chemical weathering rates and temporary and net CO2 sinksin the Bei Jiang, which was characterized as a hyperactiveregion with high chemical weathering rates, carbonate andsilicate mixing lithology, and abundant sulfuric acid chem-ical weathering agent of acid deposition and acid miningdrainage (AMD) origins. The total chemical weathering rateof 85.46 t km−2 a−1 was comparable to that of other riversin the hyperactive zones between the latitudes 0 and 30◦. Acarbonate weathering rate of 61.15 t km−2 a−1 contributed toabout 70 % of the total. The lithology, runoff, and geomor-phology had a significant influence on the chemical weath-ering rate. The proportion of carbonate outcrops had a sig-nificant positive correlation with the chemical weatheringrate. Due to the interaction between dilution and compensa-tion effect, a significant positive linear relationship was de-tected between runoff and total carbonate and silicate weath-ering rates. The geomorphology factors such as catchmentarea, average slope, and hypsometric integral value (HI)had nonlinear correlation with chemical weathering rate andshowed significant scale effect, which revealed the com-plexity in chemical weathering processes. Dissolved inor-ganic carbon (DIC) apportionment showed that CCW (car-bonate weathering by CO2) was the dominant origin of DIC(35 %–87 %). SCW (carbonate weathering by H2SO4) (3 %–15 %) and CSW (silicate weathering by CO2) (7 %–59 %)

were non-negligible processes. The temporary CO2 sink was823.41× 103 mol km−2 a−1. Compared with the temporarysink, the net sink of CO2 for the Bei Jiang was approximately23.18× 103 mol km−2 a−1 of CO2 and was about 2.82 % ofthe “temporary” CO2 sink. Human activities (sulfur acid de-position and AMD) dramatically decreased the CO2 net sink,even making chemical weathering a CO2 source to the atmo-sphere.

1 Introduction

Chemical weathering driven by weak carbonic acid (H2CO3)that originates from atmosphere CO2 or soil respiration undernatural conditions is a fundamental geochemical process reg-ulating the atmosphere–land–ocean carbon fluxes and Earth’sclimate (Guo et al., 2015). Carbonate and silicate weather-ing define the two typical categories of chemical weathering.From the view of the global carbon cycle, the CO2 consump-tion due to carbonate weathering is recognized as the “tem-porary” sink because the flux of CO2 consumed by carbonatedissolution on the continents is balanced by the flux of CO2released into the atmosphere from the oceans by carbonateprecipitation on the geological timescale (Cao et al., 2015;Garrels, 1983). The consumption of CO2 during chemicalweathering of silicate rocks has been regarded as the net sink

Published by Copernicus Publications on behalf of the European Geosciences Union.

3876 Y. Cao et al.: Temporary and net sinks of atmospheric CO2 due to chemical weathering

of CO2 and regulates the global carbon cycle (Hartmann etal., 2009, 2014b; Kempe and Degens, 1985; Lenton and Brit-ton, 2006). Thus in a carbonate–silicate mixing catchment, itis essential to distinguish proportions of the two most im-portant lithological groups, i.e., carbonates and silicates, andevaluate the net CO2 sink due to chemical weathering of sil-icate (Hartmann et al., 2009).

In addition to the chemical weathering induced by H2CO3,sulfuric acid (H2SO4) of anthropogenic origins produced bysulfide oxidation such as acid deposition caused by fossil fuelburning and acid mining discharge (AMD) also becomes animportant chemical weathering agent in the catchment scale.Many studies have shown the importance of sulfide oxida-tion and subsequent dissolution of other minerals by the re-sulting sulfuric acid at catchment scale (Hercod et al., 1998;Spence and Telmer, 2005). Depending on the fate of sul-fate in the oceans, sulfide oxidation coupled with carbon-ate dissolution could facilitate a release of CO2 to the atmo-sphere (Spence and Telmer, 2005). The carbonate weather-ing by H2SO4 plays a very important role in quantifying andvalidating the ultimate CO2 consumption rate. Thus, underthe influence of human activities, the combination of silicateweathering by H2CO3 and carbonate weathering by H2SO4controlled the net sink of atmospheric CO2.

Numerous studies on chemical weathering of larger rivershave been carried out to examine hydrochemical character-istics, chemical erosion and CO2 consumption rates, andlong-term climatic evolution of the Earth, for example forthe Yangtze River (Chen et al., 2002; Ran et al., 2010),the Huang He (Zhang et al., 1995), the Pearl River (Gao etal., 2009; Xu and Liu, 2010; Zhang et al., 2007), the HuaiRiver (Zhang et al., 2011), the rivers of the Qinghai–TibetanPlateau (Jiang et al., 2018; Li et al., 2011; Wu et al., 2008),the Mekong River (Li et al., 2014), the rivers of the Alpineregion (Donnini et al., 2016), the Sorocaba River (Fernandeset al., 2016), the rivers of Baltic Sea catchment (Sun et al.,2017), the Amazon River (Gibbs, 1972; Mortatti and Probst,2003; Stallard and Edmond, 1981; Stallard and Edmond,1983, 1987), the Lena River (Huh and Edmond, 1999), andthe Orinoco River (Mora et al., 2010). For simplicity ofcalculation, most of the research has ignored sulfuric-acid-induced chemical weathering and resulted in an overestima-tion of CO2 sink. To overcome this shortcoming of the tra-ditional mass balance method, we applied a dissolved inor-ganic carbon (DIC) source apportionment procedure to dis-criminate the contribution of sulfuric-acid-induced chemicalweathering to validate the temporary and net sink of CO2in a typical hyperactive region with carbonate–silicate mix-ing lithology to give a further understanding of basin-scalechemical weathering estimation.

About half of the global CO2 sequestration due to chemi-cal weathering occurs in warm and high-runoff regions (Lud-wig et al., 1998), called the hyperactive regions and hot spots(Meybeck et al., 2006). The Pearl River located in the sub-tropical area in south China includes three principal rivers:

the Xi Jiang, Bei Jiang, and Dong Jiang. The warm and wetclimatic conditions make the Pearl River a hyperactive re-gion in China. The three river basins have distinct geologicalconditions. The Xi Jiang is characterized as the carbonate-dominated area, and the Dong Jiang has silicate as the mainrock type. The Bei Jiang, which is the second largest tributaryof the Pearl River, is characterized as a typical carbonate–silicate mixing basin. In addition, as the severe acid deposi-tion (Larssen et al., 2006) and active mining area (Li et al.,2019), chemical weathering induced by sulfuric acid make itnecessary to reevaluate the temporary and net sinks of atmo-spheric CO2. Thus, the Bei Jiang in southeast China with atypical subtropical monsoon climate and carbonate–silicatemixing geologic settings was selected as the study area. Thethree main objectives are summarized as follows: (1) revealspatial–temporal variations in major element chemistry ofthe river water, (2) calculate the chemical weathering rateand unravel the controlling factors on chemical weatheringprocesses, and (3) determine the temporary sink of CO2 andevaluate the influence of sulfide oxidation on the net sink ofCO2 by DIC apportionment.

2 Study area

The Bei Jiang basin, which is the second largest tributaryof the Pearl River basin, is located in the southeast of China(Fig. 1). It covers an area of 52 068 km2 and has a total lengthof 573 km. The river basin is located in subtropical monsoonclimate zone, with the mean annual temperature across thedrainage basin ranging from 14 to 22 ◦C and the mean annualprecipitation ranging from 1390 to 2475 mm. The averageannual runoff is 51×109 m3, with 70 %–80 % of the flux oc-curring from April to September. This can be attributed to thefact that more than 70 % of the annual precipitation (about1800 mm yr−1) is concentrated in the wet season (April toSeptember).

Lithology in the river basin is composed of limestone,sandstone, gneiss, and glutenite. In the upper basin, carbon-ate rock (mainly of limestone) outcrops in the west and cen-ter, while sandstone of the Devonian era and mudstone ofthe Paleogene era outcrop in the east of the upper stream.In the middle of basin, limestone and sandstone cover mostof the area, and Cretaceous volcanic rocks are found in thetributary (Lian Jiang), mainly granite. In the lower basin,Archean metamorphic rocks outcrop in the west and are com-posed of gneiss and schist; sandstone covers the rest of areaof the lower basin. Quaternary sediments are scattered alongthe main stream of the river. The carbonate and silicate rockoutcrops in the Bei Jiang basin are 10 737 km2 (28 %) and24 687 km2 (65 %), respectively.

Biogeosciences, 17, 3875–3890, 2020 https://doi.org/10.5194/bg-17-3875-2020

Y. Cao et al.: Temporary and net sinks of atmospheric CO2 due to chemical weathering 3877

Figure 1. Geology map and sampling point in the Bei Jiang basin(produced by ArcGIS).

3 Materials and methods

3.1 Sampling procedure and laboratory analysis

Water samples were collected monthly at 15 hydrologic sta-tions from January to December in 2015 (Fig. 1). The riverwaters were sampled by a portable organic class water sam-pler along the middle thread of the channel on the first dayof each month. In addition, to discriminate the contributionof rain inputs, the daily rainwater was also sampled at fivestations (SJs, FLXs, YDs, XSs, and XGLs) along the mainstream. The rainwater collector is consisted of a funnel witha diameter of 20 cm and a 5 L plastic bottle. A rubber ballis set up in the funnel to prevent evaporation. All the riverand rainwater were filtered through a 0.45 µm glass fiber fil-ter and stored in 100 mL tubes and stored below 4 ◦C untilanalysis.

Electric conductivity (EC), pH, and temperature (T )were measured using a multi-parameter water quality meter(HACH-HQ40Q), and alkalinity (HCO−3 ) was measured infiltered water samples by titration in situ. The dissolved SiO2was measured with the molybdenum yellow method and wasanalyzed using an ultraviolet spectrophotometer (ShimadzuUV-2600). The cations (Na+, K+, Ca2+, Mg2+) and an-ions (Cl−, SO2−4 ) were analyzed with ion chromatography(Thermo Fisher ICS-900) with a limit of detection (L.O.D) of0.01 mg L−1. Reference, blank, and replicate samples were

employed to check the accuracy of all the analyses, and therelative standard deviations of all the analyses were within±5 %. The electrical balance (E.B.) defined by the equationE.B.= meq(sum of cations)−meq(sum of anions)meq(sum of cations and anions) × 100 of the watersamples was less than 5 %.

3.2 Calculation procedure

3.2.1 Chemical weathering rates

The mass balance equation for element X in the dissolvedload can be expressed as (Galy and France-Lanord, 1999)

[X]riv = [X]pre+ [X]eva+ [X]sil+ [X]car+ [X]anth. (1)

Here [X] denotes the elements of Ca2+, Mg2+, Na+, K+,Cl−, SO2−4 , and HCO

−

3 in millimoles per liter. The subscriptsriv, pre, eva, sil, car, and anth denote the river, precipitationsource, evaporite source, silicate source, carbonate source,and anthropogenic source.

In the study area, the anthropogenic source of majorions except for SO2−4 was ignored due to the followingtwo reasons. (1) Two main characteristics of much-pollutedrivers are that total dissolved solid (TDS) is greater than500 mg L−1 and the Cl−/Na+ molar ratio is greater thanthat of sea salts (about 1.16) (Cao et al., 2016a; Gaillardetet al., 1999). The TDS in the study area ranged from 73.79to 230.16 mg L−1, and the low TDS implied that the anthro-pogenic origins of major ions could be ignored in the study.However, the Bei Jiang is characterized as a typical regionsuffering from severe acid deposition (Larssen et al., 2006)and are active mining area (Li et al., 2019). The acid deposi-tion and acid mining discharge contribute to the highest con-centration of SO2−4 . (2) Natural origin of SO

2−4 is the disso-

lution of evaporite, such as gypsum, while no evaporite wasfound in the study area. If SO2−4 comes from the gypsumdissolution, the ratios of Ca2+ and SO2−4 should be close to1 : 1. The stoichiometric analysis (Fig. 2) showed that the ra-tio of Ca2+ and SO2−4 deviated from 1 : 1 and also proved thispoint.

Therefore, on the basis of the theory of rock chemicalweathering and ignoring the anthropogenic origins of majorions (except for SO2−4 ), the major elements of river water canbe simplified as follows.

[Cl−]riv = [Cl−]pre+ [Cl−]eva (2)[K+]riv = [K+]pre+ [K+]sil (3)[Na+]riv = [Na+]pre+ [Na+]eva+ [Na+]sil (4)

[Ca2+]riv = [Ca2+]pre+ [Ca2+]sil+ [Ca2+]car (5)

[Mg2+]riv = [Mg2+]pre+ [Mg2+]sil+ [Mg2+]car (6)

[HCO−3 ]sil = [K+]sil+ [Na+]sil+ 2[Mg2+]sil

+ 2[Ca2+]sil (7)[HCO−3 ]car = [HCO

−

3 ]riv− [HCO−

3 ]sil (8)

https://doi.org/10.5194/bg-17-3875-2020 Biogeosciences, 17, 3875–3890, 2020


Figure 2. Stoichiometric relationship between Ca2+ and SO2−4 .The “SCW” means carbonate weathering induced by sulfuric acid.

[SO2−4 ]riv = [SO2−4 ]pre+ [SO

2−4 ]anth (9)

Firstly, the measured ion concentrations of the rainwater arerectified by evaporation coefficient α = 0.63= P/R (with Pthe precipitation and R the runoff), and the contributions ofatmospheric precipitation are calculated. Secondly, the mo-lar ratios of Ca2+/Na+ (0.4) and Mg2+/Na+ (0.2) for thesilicate end-member (Zhang et al., 2007) are used to calcu-late the contribution of Ca2+ and Mg2+ from silicate weath-ering, and then, residual Ca2+ and Mg2+ were attributed tocarbonate weathering. For monthly data, the contributions ofdifferent sources can be calculated as follows.

Rcar =([Ca2+]car+ [Mg2+]car

)/S× 100% (10)

Rsil =([K+]sil+ [Na+]sil+ [Ca2+]sil

+ [Mg2+]sil)/S× 100% (11)

Reva = [Na+]eva/S× 100% (12)

Rpre =([K+]pre+ [Na+]pre+ [Ca2+]pre

+ [Mg2+]pre)/S× 100% (13)

S = [Ca2+]car+ [Mg2+]car+ [Ca2+]sil+ [Mg2+]sil

+ [Na+]sil+ [K+]sil+ [Na+]eva+ [Ca2+]pre

+ [Mg2+]pre+ [Na+]pre+ [K+]pre (14)

HereR denotes the proportions of dissolved cations from dif-ferent sources. S denotes the total concentrations of cationsfor river water in millimoles per liter.

The total, carbonate and silicate chemical weathering rates(TWR, CWR, and SWR) of a year can be estimated as fol-lows.

CWR=n=12∑i=1

[(24×[Mg2+]car+ 40×[Ca2+]car

+ 61×[HCO−3 ]car× 0.5)i×Qi/(106A)

](15)

SWR=n=12∑i=1

[(39×[K+]sil+ 23×[Na+]sil

+ 24×[Mg2+]sil+ 40×[Ca2+]sil

+ 96×[SiO2]sil)i×Qi/(106A)

](16)

TWR= CWR+SWR (17)

Here TWR, CWR, and SWR in metric tons per square kilo-meter per year, Qi denotes discharge in cubic meters permonth, and A denotes the catchment area in square kilome-ters.

3.2.2 DIC apportionments

In the Bei Jiang, the pH values of water samples ranged from7.5 to 8.5 with an average of 8.05. Under these pH condi-tions, the major species of DIC is HCO−3 . In addition, HCO

−

3accounted for more than 95 % at all sampling sites basedon calculation; thus the concentration of HCO−3 (mmol L

−1)was used to represent the DIC concentration in this study.The riverine DIC originates from several sources includingcarbonate minerals, respired soil CO2, and atmospheric CO2,and it could be affected by processes occurring along the wa-ter pathways (Khadka et al., 2014; Li et al., 2008). Four dom-inant weathering processes, including (1) carbonate weather-ing by carbonic acid (CCW), (2) carbonate weathering bysulfuric acid (SCW), (3) silicate weathering by carbonic acid(CSW), (4) and silicate weathering by sulfuric acid (SSW),can be described by the following reaction equations.

CCW :(Ca2−XMgx

)(CO3)2+ 2H2CO3

→ (2− x)Ca2++ xMg2++ 4HCO−3 (R1)

SCW :(Ca2−XMgx

)(CO3)2+H2SO4

→ (2− x)Ca2++ xMg2++ 2HCO−3 +SO2−4 (R2)

CSW :CaSiO3+ 2H2CO3+H2O

→ Ca2++H4SiO4+ 2HCO−3 (R3)

SSW :CaSiO3+H2SO4+H2O

→ Ca2++H4SiO4+SO2−4 (R4)

Here CaSiO3 represents an arbitrary silicate.According to the study of Galy and France-Lanord (1999)

and Spence and Telmer (2005), carbonate and silicate weath-ering by carbonic acid have the same ratio as carbonate andsilicate weathering by sulfuric acid, and for monthly data themass balance equations are as follows:

[SO2−4 ]riv− [SO2−4 ]pre = [SO

2−4 ]SCW+ [SO

2−4 ]SSW, (18)

[SO2−4 ]riv− [SO2−4 ]pre = αSCW×[HCO

−

3 ]riv× 0.5

+αCSW×αSCW

αCCW×[HCO−3 ]riv, (19)

where the subscripts CCW, SCW, CSW, and SSW denotethe four end-members defined by carbonate weathering by



carbonic acid, carbonate weathering by sulfuric acid, silicateweathering by carbonic acid, and silicate weathering by sul-furic acid, respectively. The parameter α denotes the propor-tion of DIC derived from each end-member process.

According to the above description, the ion balance equa-tions are as follows.

[Ca2+]car+ [Mg2+]car = αCCW×[HCO−3 ]riv× 0.5

+αSCW×[HCO−3 ]riv (20)

[SO2−4 ]SCW+ [SO2−4 ]SSW = αSCW×[HCO

−

3 ]riv× 0.5

+αCSW×αSCW

αCCW×[HCO−3 ]riv (21)

αCCW+αSCW+αCSW = 1 (22)

Combining the above equations, the proportions of HCO−3derived from the three end-members (CCW, SCW, and CSW)can be calculated, and the DIC (equivalent to HCO−3 ) fluxesby different chemical weathering processes are calculated bythe following equations.

[HCO−3 ]CCW = αCCW×[HCO−

3 ]riv (23)[HCO−3 ]SCW = αSCW×[HCO

−

3 ]riv (24)[HCO−3 ]CsW = αCSW×[HCO

−

3 ]riv (25)

3.2.3 CO2 consumption rate and CO2 net sink

According to the Reactions (R1)–(R4), only the processes ofCCW and CSW can consume the CO2 from the atmosphereor soil and only half of the HCO−3 in the water due to car-bonate weathering by carbonic acid from atmospheric CO2.Thus, the CO2 consumption rates (CCRs) for CCW and CSWcan be calculated as follows (Zeng et al., 2016).

CCRCCW =n=12∑i=1

{[0.5× (Q/A)×[HCO−3 ]CCW]/1000

}i

(26)

CCRCSW =n=12∑i=1

{[(Q/A)×[HCO−3 ]CSW]/1000

}i

(27)

Here Q is discharge in cubic meters per year, [HCO−3 ] isconcentration of HCO−3 in millimoles per liter, and A iscatchment area in square kilometers, so that the CCR is in103 mol km−2 a−1.

According to the classical view of the global carbon cy-cling (Berner and Kothavala, 2001), the CCW is not a mech-anism that can participate in the amount of CO2 in the at-mosphere because all of the atmospheric CO2 fixed throughCCW is returned to the atmosphere during carbonate precip-itation in the ocean. However, when sulfuric acid is involvedas a proton donor in carbonate weathering, half of the dis-solved carbon is re-released to the atmosphere during carbon-ate precipitation. Thus, SCW leads to a net release of CO2 inthe ocean–atmosphere system over a timescale typical of res-idence times of HCO−3 in the ocean (10

5 years). Meanwhile,

in the case of CSW, followed by carbonate deposition, 1 ofthe 2 mol of CO2 involved is transferred from the atmosphereto the lithosphere in the form of carbonate rocks, while theother 1 mol returns to the atmosphere, resulting in a net sinkof CO2. Therefore, the net CO2 consumption rate (CCRNet)due to chemical weathering can be concluded as follows.

CCRNet =n=12∑i=1

{[(0.5×[HCO−3 ]CSW− 0.5

×[HCO−3 ]SCW)× (Q/A)

]/1000

}i

(28)

3.3 Spatial and statistical analysis

The hypsometric integral value (HI) (Pike and Wilson, 1971)was employed in this study to evaluate the influence of ter-rain on the chemical weathering. HI is an important indexto reveal the relationship between morphology and develop-ment of landforms and can be used to establish the quan-titative relationship between the stage of geomorphologicaldevelopment and the material migration in the basin (Pikeand Wilson, 1971; Singh et al., 2008; Strahler, 1952). The HIvalue of each watershed is calculated by the elevation / reliefratio method and can be obtained by the following equation(Pike and Wilson, 1971):

HI=Mean.elevation−Min.elevationMax.elevation−Min.elevation

, (29)

Here HI is the hypsometric integral, Mean.elevation is themean elevation of the watershed, Min.elevation is the min-imum elevation within the watershed, and Max.elevation isthe maximum elevation within the watershed. According tothe hypsometric integral value (HI), the geomorphologicaldevelopment can be divided into three stages: nonequilib-rium or young stage (HI> 0.6), equilibrium or mature stage(0.35


4 Results

4.1 Chemical compositions

The major physical–chemical parameters of river water sam-ples are presented in Table 1. In Table 1, the chemical pa-rameters of river water are the flow-weighted average over12 months. For every sampling station, the flow-weightedaverage of ion concentration can be expressed followed

the equation [X]avarage =

n=12∑i=1[X]i×Qi

n=12∑i=1

Qi

, where [X] denotes

the elements of Ca2+, Mg2+, Na+, K+, Cl−, SO2−4 , andHCO−3 in millimoles liters. Q denotes average monthly dis-charge in cubic meters per second. The subscripts i de-notes 12 months from January to December. For all themonthly samples, the pH values ranged from 7.5 to 8.5 withan average of 8.05. Average EC was 213 µs cm−1, rang-ing from 81 to 330 µs cm−1. The TDS of river water sam-ples varied from 73.8 to 230.2 mg L−1, with an average of157.3 mg L−1, which was comparable with the global aver-age of 100 mg L−1 (Gaillardet et al., 1999). Compared withthe major rivers in China, the average TDS was significantlylower than the Yangtze (Chen et al., 2002), the Huang He(He et al., 2017) the Zhu Jiang (Zhang et al., 2007), theHuai He (Zhang et al., 2011), and the Liao He (Ding etal., 2017). However, the average TDS was higher than therivers draining silicate-rock-dominated areas, e.g., the DongJiang (59.9 mg L−1) in southern China (Xie et al., 2013), theNorth Han River (75.5 mg L−1) in South Korea, (Ryu et al.,2008), the Amazon River (41 mg L−1), and the Orinoco River(82 mg L−1) draining the Andes (Dosseto et al., 2006; Ed-mond et al., 1996).

Major ion compositions are shown in the Piper plot(Fig. 3). Ca2+ was the dominant cation with concentrationranging from 199 to 1107 µmol L−1, accounting for approxi-mately 49 % to 81 %, with an average of 66 % (µEq) of the to-tal cation composition in the river water samples. HCO−3 wasthe dominant anion, with concentration ranging from 640 to2289 µmol L−1. On average, it comprised 77 % (59 %–92 %)of total anions, followed by SO2−4 (16 %) and Cl

− (6 %). Themajor ionic composition indicated that the water chemistryof the Bei Jiang basin was controlled by both carbonate andsilicate weathering.

The PCA was used to extract the factors controlling thechemical compositions. The varimax rotation was used to re-duce the number of variables to two principal components(PCs), which together explain 76.88 % of the total variancein the data. The first PC (PC1) explained approximately50.02 % of the total variations and was considered to rep-resent the carbonate weathering factor because of the highloadings of EC, TDS, Ca2+, Mg2+, and HCO−3 concentra-tions. The second PC (PC2) explained 26.85 % of the totalvariance and presented high loadings for Na+ and K+ con-

Figure 3. Piper plot of river water samples in the Bei Jiang.

centrations. Thus, the PC2 represented a silicate weatheringfactor. These two PCs were considered to be two importantsources of major ions in the Bei Jiang basin.

The hydrochemical compositions of rainwater are pre-sented in Table S1 in the Supplement. Ca2+ was thedominant cation with concentration ranging from 6.9 to282.6 µmol L−1, accounting for approximately 65 % of thetotal cation composition in the rainwater samples. SO2−4 wasthe dominant anion, with concentration ranging from 21.9to 1462 µmol L−1, accounting for approximately 67 % of thetotal anion composition in the rainwater samples.

4.2 Seasonal and spatial variations

There were significant seasonal variations in the major ionconcentrations (Fig. 4). Two basic patterns of temporal vari-ations could be observed. The first one was related to thecarbonate-weathering-derived ions such as Ca2+ and HCO−3 ,which showed high values in November and low values inJune. The second one was for the silicate-weathering-derivedions such as Na+ and K+, which showed high values inFebruary and low values in June. The minimums occurredin June, and all the ions showed a significant dilution effectduring the high-flow periods.

It was clear that the Ca2+ and HCO−3 concentrations had adecreasing trend from upstream to downstream (Fig. 5); thischaracteristic agrees with the trends observed in the YangtzeRiver and the Huai River, where the major elements or TDSconcentrations of the main channel showed a general de-creasing trend, and the tributaries display the dilution effectto the main channel. For other silicate-weathering-derivedions such as Na+, there was a slight increasing trend im-plying the chemical inputs from the tributaries. These trendswere in accordance with the lithology in the study area. The



Table 1. The major physical–chemical parameters of river water samples at 15 hydrological stations in the Bei Jiang (mean±SD). The totaldissolved solid (TDS, mg L−1) expressed as the sum of major inorganic species concentrations (Na++K++Ca2++Mg2++HCO−3 +

Cl−+SO2−4 +NO−

3 +SiO2).

Hydrological pH EC TDS Na+ K+ Ca2+ Mg2+ HCO−3 Cl− SO2−4 SiO2 HI

stations (µs cm−1) (mg L−1) (µmol L−1)

JLWs 7.9± 0.2 95± 40 81.1± 25.6 111.4 51.9 223.5 103.9 701.9 28.3 44.5 225.2 0.34CXs 8.2± 0.2 219± 50 163.7± 20.9 118.1 40.1 793.3 187.1 1593.6 60.5 199.4 106.3 0.29HJTs 8.1± 0.2 203± 34 151.8± 21.9 100.2 29.9 686.7 203.9 1708.7 29.5 72.2 156.6 0.30ZKs 8.1± 0.1 218± 45 161.3± 21.1 426.4 66.2 560.3 134.1 1276.9 134.7 161.4 151.9 0.22XGLs 7.8± 0.2 168± 16 117.9± 8.9 315.4 112.4 422.4 101.0 992.2 213.9 112.6 178.9 0.18WJs 8.1± 0.1 260± 27 172.9± 16.7 197.8 59.0 767.3 122.6 1467.1 99.1 162.8 183.4 0.25LXs 8.1± 0.2 236± 33 171.8± 19.6 122.1 38.1 813.5 176.0 1829.4 51.5 89.2 145.7 0.21LCs 8.2± 0.1 253± 26 196.1± 20.0 287.4 46.8 862.6 234.4 1845.7 115.7 232.4 130.7 0.27LSs 8.3± 0.1 220± 46 184.2± 18.3 258.9 58.2 793.5 202.9 1740.6 109.0 191.9 121.4 0.25XSs 7.9± 0.1 156± 30 123.9± 17.6 305.0 86.1 366.8 110.9 966.6 103.8 166.5 218.7 0.24GDs 8.1± 0.1 232± 11 169.4± 8.3 112.6 40.5 781.6 172.1 1798.5 44.0 90.3 141.2 0.24SKs 8.1± 0.2 238± 22 161.1± 17.4 345.3 73.6 641.0 162.5 1304.1 174.4 223.5 160.1 0.21Yds 7.8± 0.2 241± 54 165.9± 34.0 296.4 59.3 674.8 160.9 1515.0 118.7 175.9 144.4 0.21FLXs 8.0± 0.2 232± 37 161.4± 22.8 187.6 95.1 577.0 135.0 1262.4 111.9 159.6 169.5 0.21SJs 8.1± 0.1 230± 27 176.4± 18.9 355.0 83.4 663.5 156.2 1367.7 182.4 190.5 180.5 0.21

Figure 4. Monthly variations in environmental parameters and major ion concentrations in the Bei Jiang basin (SJs station). The columnsdenote the monthly discharge.

carbonate dominates in the upper stream basin; when theriver drains this area, carbonate weathering contributes to theelevation of Ca2+ and HCO−3 . As the river enters into thedownstream dominated by silicate, the relatively low ion con-centrations due to silicate weathering contributed to dilutingthe Ca2+ and introducing extra Na+ to the main channel.

5 Discussion

5.1 Chemical weathering rates and the controllingfactors

5.1.1 Chemical weathering rates

Atmospheric precipitation inputs, anthropogenic inputs (herereferring to the acid deposition and AMD), and chemicalweathering of rocks and minerals are the major sources con-tributing to the hydrochemistry in the river basin. Previous



Figure 5. Spatial variations in major ion and SiO2 concentrations inthe Bei Jiang basin (from upstream station CXs to the downstreamstation SJs).

studies have shown that rock weathering contributions to ma-jor element compositions of the river can be interpreted interms of mixing among three main end-members: the weath-ering products of carbonates, silicates, and evaporites (Cao etal., 2016b; Négrel et al., 1993; Ollivier et al., 2010). The riverwater samples in the Bei Jiang basin are displayed on theplots of Na-normalized molar ratios (Fig. 6). In these plots,the contributions from carbonate weathering correspond tothe trend toward the high-Ca2+ end-member close to thetop right corner, while silicate weathering corresponds to thetrend toward the high-Na+ end-member close to the lowerleft corner. It was clear that the samples with high ratio ofcarbonate outcrop had the highest molar ratios of Ca2+/Na+,Mg2+/Na+, and HCO−3 /Na

+, which were the samples lo-cated toward the carbonate weathering end-member. How-ever, the samples with low Ca2+/Na+, Mg2+/Na+, andHCO−3 /Na

+ ratios showed the influence of silicate weath-ering. In addition, major ion compositions of the Bei Jiangwere mainly contributed by the weathering of carbonates andsilicates and showed little contribution of evaporite weather-ing.

Based on the chemical balance method, the calculated con-tributions of different sources to the total cationic loads arepresented in Fig. 7. The results show that carbonate weath-ering was the most important mechanism controlling the lo-cal hydrochemistry and contributed approximately 50.06 %(10.96 %–79.96 %) of the total cationic loads. Silicate weath-ering and atmospheric precipitation inputs accounted for25.71 % (5.55 %–70.38 %) and 17.92 % (0 %–46.95 %), re-spectively. Evaporite weathering had the minimum contribu-tion with an average of 6.31 % (0 %–24.36 %) to the totalcationic loads.

The result of chemical weathering rates is listed in Table 2.The carbonate weathering contributes about 70 % of the totalchemical weathering, and the averages of carbonate and sil-icate weathering rate in the Bei Jiang basin were 61.15 and

25.31 t km−2 a−1, respectively. In addition, chemical weath-ering rates showed significant seasonal variations, with thehighest carbonate and silicate weathering rates in May (16.75and 5.50 t km−2 per month, respectively) and the lowest car-bonate and silicate weathering rates in February (0.95 and0.39 t km−2 per month, respectively). Gaillardet et al. (1999)reported the chemical weathering rate of major rivers all overthe world and found that the hyperactive zone with a highchemical weathering rate is generally located between thelatitude 0 and 30◦ and our study belongs to this area (Fig. 8).The factors influencing the balance between CWR and SWRwill be further discussed in the following sections.

5.1.2 Factors affecting chemical weathering

Many factors control the chemical weathering rates, includ-ing terrain, geotectonic properties, lithology, land cover, cli-matic conditions (temperature, precipitation, etc.), and hy-drological characteristics (Ding et al., 2017; Gislason et al.,2009; Hagedorn and Cartwright, 2009). For this study, thelithology, hydrological characteristics, and geomorphologywere selected as the major factors to be discussed.

Lithology

Among all the factors controlling the chemical weatheringrates, lithology is one of the most important factors becausedifferent types of rocks have different weathering abilities(Viers et al., 2014). The TWR had a significant positive cor-relation (p < 0.01) with the ratios of the proportion of car-bonate and a nonsignificant positive correlation with that ofsilicate outcrops (Fig. 9a, b). Furthermore, a significant cor-relation (p < 0.01) was found between the CWR and pro-portion of carbonate outcrops (Fig. 9c), but the correlationbetween the SWR and the proportion of silicate outcrops waslow and not statistically significant (p > 0.05, Fig. 9d). Thecorrelation analysis confirmed that carbonate outcrop ratioswere the sensitive factor controlling the chemical weatheringrates, and the rapid kinetics of carbonate dissolution playedan important role in weathering rates in the Bei Jiang basin.

Runoff

Chemical weathering is a combination of two processes, in-cluding dissolution of primary minerals and precipitation ofsecondary mineral growth (Eiriksdottir et al., 2011; Hart-mann et al., 2014a; Liu et al., 2013). The dissolution processis related to precipitation and runoff. In general, river waterchemistry is usually diluted by river runoff (Q), and this di-lution effect is variable in different basins (Rao et al., 2019).The dilution effects of major elements caused by increasingwater flow can be expressed by a log linear equation, thestandard rating relationship (Li et al., 2014; Walling, 1986;Zhang et al., 2007):

Ci = aQb, (30)



Figure 6. Mixing diagrams using Na-normalized molar ratios: (a) Mg2+/Na+ vs. Ca2+/Na+ and (b) HCO−3 /Na+ vs. Ca2+/Na+ for the

Bei Jiang basin. The color ramp showed the percentage of carbonate outcrops.

Table 2. The annual discharge, catchment area, carbonate and silicate outcrop proportions, and calculated weathering rates of carbonate andsilicate of 15 subcatchments in the Bei Jiang.

ID Annual Catchment Percentages Percentages Carbonate weathering Silicate weathering Total weatheringdischarge area (km2) of carbonate of silicate rate, CWR rate, SWR rate, TWR

(108 m3 a−1) (%) (%) (t km−2 yr−1) (t km−2 yr−1) (t km−2 yr−1)

JLWs 2.23 281.13 2.95 97.05 18.63 14.94 33.56CXs 4.06 392.35 57.44 42.56 74.21 11.42 85.64HJTs 11.54 503.02 41.99 55.83 169.12 29.73 198.85ZKs 16.38 1655.22 34.60 61.81 35.03 24.14 59.17XGLs 13.56 1863.02 0.38 93.07 25.75 13.96 39.72WJs 19.11 1960.99 12.51 73.87 55.00 17.43 72.43LXs 56.37 2458.06 34.32 64.07 178.71 29.39 208.10LCs 58.74 5278.14 49.67 50.21 79.70 20.59 100.29LSs 74.83 6994.69 44.59 52.44 69.28 14.94 84.22XSs 62.11 7497.01 7.09 87.81 18.85 20.35 39.20GDs 137.81 9028.38 49.93 44.93 111.73 19.19 130.92SKs 49.51 17 417.24 25.43 69.35 12.71 6.11 18.82YDs 191.07 18 234.64 25.63 68.05 52.37 19.59 71.95FLXs 396.25 34 232.34 29.68 63.49 68.38 17.53 85.91SJs (average) 450.90 38 538.06 28.12 64.65 61.15 25.31 86.46

where Ci is the concentration of element i (mmol L−1), Q isthe water discharge (m3 s−1), a is the regression constant,and b is the regression exponent. The linear fitting resultis shown by Fig. 10, and the parameters b for major ele-ments obtained from the dataset were 0.08 (Na+), 0.05 (K+),0.08 (Ca2+), 0.02 (Mg2+), 0.06 (HCO−3 ), 0.12 (Cl

−), 0.11(SO2−4 ), and −0.005 (SiO2). In many cases, b ranges from−1 to 0 due to the chemical variables that are influenced invarious ways and various extents. However, in our study area,the values of b were positive and not comparable to the ob-servations in major Asian rivers such as the Yangtze (Chen etal., 2002), the Yellow (Chen et al., 2005), the Pearl (Zhang etal., 2007), and the Mekong (Li et al., 2014). This suggestedadditional and significant solute sources in the river basin thatmight contribute to and compensate for the effect of dilutionby precipitation. The difference of slope for individual dis-

solved components at different stations reflected the differentsources and the solubility of source materials.

Due to the compensation effect of chemical weathering,significant positive linear relationship was detected betweenQ and TWR, CWR, and SWR. Thus, the linear regressionanalyses between Q and TWR, CWR, and SWR were con-ducted to further reveal the effect of runoff on chemicalweathering rate. The slope of the liner regression equationsfor all 15 hydrological station watersheds in the Bei Jiangbasin are summarized in Table 3. The linear relations indi-cated that the increase in runoff could accelerate the chemi-cal weathering rates, but the variations in K values revealedthat the degrees of influences were different due to multiplefactors, such as the influence of geomorphology.



Table 3. The slope of the liner regression equation between runoff (Q) and total weathering rate (TWR), carbonate weathering rate (CWR),and silicate weathering rate (SWR).

Hydrological Total weathering Carbonate weathering Silicate weatheringstations rate, K1Q rate, K2Q rate, K3Q

K1 R2 K2 R

2 K3 R2

JLWs 0.3912 0.99 0.2091 0.99 0.1821 0.99CXs 0.6492 0.93 0.5631 0.93 0.0860 0.94HJTs 0.5117 0.97 0.4421 0.96 0.0695 0.99ZKs 0.0953 0.97 0.0525 0.76 0.0429 0.80XGLs 0.0835 0.98 0.0558 0.97 0.0278 0.98WJs 0.1017 0.99 0.0842 0.99 0.0175 0.88LXs 0.0968 0.98 0.0843 0.98 0.0125 0.99LCs 0.0486 0.90 0.0401 0.87 0.0085 0.97LSs 0.0359 0.97 0.0286 0.96 0.0073 0.94XSs 0.0180 0.98 0.0080 0.97 0.0100 0.96GDs 0.0252 0.99 0.0216 0.99 0.0036 0.99SKs 0.0116 0.98 0.0083 0.98 0.0033 0.95Yds 0.0106 0.99 0.0081 0.99 0.0026 0.92FLXs 0.0050 0.97 0.0039 0.95 0.0010 0.99SJs 0.0053 0.99 0.0037 0.97 0.0016 0.98

Figure 7. Calculated contributions (%) from the different hydro-logical stations to the total cationic load in the Bei Jiang basin. Thecationic loads were the sum of Na+, K+, Ca2+, and Mg2+.

Geomorphology

The geomorphology factors including catchment area, aver-age slope, and HI, which could influence the runoff genera-tion process and physical and chemical weathering, were se-lected to give a further explanation of the variation in K val-ues. As shown in Fig. 11a, the K values were found to havea nonlinear relationship with the areas of subcatchment andcould be fitted by an exponential decay model, which showedthat the K values decreased dramatically with the initial in-crease in area and quickly become stable after reaching the

Figure 8. Relationship between latitude and total weathering rate(TWR).

threshold. The threshold value forK1,K2, andK3 was about5000 km2. This indicated that the compensation effect wasmore significant in small catchments.

The average topographic slope of each subcatchmentranged from 37 to 63◦. With the increasing average slope,the residence time of both surface water and groundwaterdecreases. Kinetics of carbonate and silicate reactions wasdetermined by the reaction time, which could be related bythe residence time of water. In our study area, the K val-ues showed nonlinear negative correlation with average slope(Fig. 11e, f, g). When the average slope increases, the re-sulting small residence time (time of water–rock reactions)makes the compensation effect weak in the study area.



Figure 9. The relationships between weathering rates and the pro-portions of carbonate or silicate outcrops.

Figure 10. The relationship between major ion concentrations andrunoff (Q) in logarithmic scales.

Hypsometric analysis showed that the HI ranged from0.18 to 0.34. According to the empirical classification by HI(HI> 0.6, nonequilibrium or young stage; 0.35


Figure 11. The relationships between K values and catchment area (a, b, c), average slope (d, e, f), and HI (g, h, i) for the Bei Jiang.

5.2.2 Temporary and net CO2 sink

According to the classical view of the global carbon cy-cling (Berner and Kothavala, 2001), the CO2 sink inducedby chemical weathering varies for different timescales. Ata short-term timescale, carbonic-acid-based carbonate andsilicate weathering (CCW and CSW) and transport of theHCO−3 to oceans through rivers is an important temporarycarbon sink (Khadka et al., 2014) and can be calculated bythe sum of CCRCCW and CCRCSW. Thus, it was significantto estimate the CCR of CCW and CSW (Liu and Dreybrodt,2015; Liu et al., 2011). However, at the geological timescale(> 106 years), over the timescale typical of the residencetime of HCO−3 in the ocean (10

5 years), the CCW is not amechanism that can participate in the net sink of CO2 in theatmosphere because all of the atmospheric CO2 fixed throughCCW is returned to the atmosphere during carbonate precip-itation in the ocean. Meanwhile, in the case of CSW, fol-lowed by carbonate deposition, 1 of the 2 mol of CO2 in-volved is transferred from the atmosphere to the lithospherein the form of carbonate rocks, while the other 1 mol returnsto the atmosphere. The CSW is recognized as the net sinkof atmosphere CO2. In addition, when sulfuric acid is in-volved as a proton donor in carbonate weathering, half ofthe carbon is dissolved to the atmosphere during carbonateprecipitation. Thus, SCW leads to a net release of CO2 in theocean–atmosphere system. Thus the net CO2 sink (expressed

Figure 12. Correlations between CO2 net sinks and proportionsof carbonate (a) and correlations between CO2 net sinks and[SO2−4 ]SCW or [SO

2−4 ]SSW (b).

by CCRNet in this study) is controlled by the DIC apportion-ment according to Eq. (28).

The results of CCRTotal, CCRCCW, CCRCSW, andCCRNet were summarized in Table 4. The CCRTotalwas 823.41× 103 mol km−2 a−1. Comparing with otherChinese rivers, such as the Songhua River (189×103 mol km−2 a−1) (Cao et al., 2015) and other rivers cal-culated by Gaillardet et al. (1999) including the HeilongRiver (53× 103 mol km−2 a−1), the Yangtze River (609×103 mol km−2 a−1), the Huang He (360×103 mol km−2 a−1),the Xi Jiang (960× 103 mol km−2 a−1), the Jinsha Jiang(420× 103 mol km−2 a−1), the Langcang Jiang (980×



Table 4. Calculated CO2 consumption rate and net sink of 15 nested subcatchments in the Bei Jiang basin.

Hydrological DIC apportionment Temporary sink Net sinkstations (109 mol a−1) (CO2 consumption rate) (103 mol km−2 a−1)

(103 mol km−2 a−1) CCRNet

CCW SCW CSW CCRCCW CCRCSW CCRTotal

JLWs 0.10 0.00 0.05 175.23 191.14 366.36 87.73CXs 0.57 0.04 0.05 732.05 118.18 850.23 13.18HJTs 1.57 0.06 0.34 1563.64 683.41 2247.05 286.14ZKs 1.24 0.16 0.73 375.23 439.77 815.00 172.27XGLs 0.85 0.14 0.37 227.05 195.91 422.95 61.59WJs 1.76 0.17 0.87 449.32 443.18 892.50 177.50LXs 7.30 0.40 2.61 1485.45 1060.45 2545.91 449.09LCs 8.07 0.86 1.92 764.32 363.41 1127.95 99.77LSs 10.13 0.42 2.48 724.55 354.32 1078.64 147.05XSs 2.08 0.41 3.52 138.64 469.09 607.73 207.05GDs 16.48 0.71 7.60 912.73 841.82 1754.55 381.36SKs 4.00 0.72 1.74 114.77 100.23 215.00 29.55YDs 14.11 1.75 13.10 386.82 718.64 1105.45 311.14FLXs 40.38 7.74 4.46 589.77 130.45 720.23 −47.73SJs 41.36 9.27 11.05 536.59 286.82 823.41 23.18

103 mol km−2 a−1), the Nu Jiang (1240×103 mol km−2 a−1),the Yalong Jiang (870× 103 mol km−2 a−1), the DaduHe (1280× 103 mol km−2 a−1), and Min Jiang (660×103 mol km−2 a−1), our study area showed relatively highCCR due to a high chemical weathering rate. In addition,the CCRCCW and CCRCSW were 536.59× 103 (65 %) and286.82× 103 (35 %) mol km−2 a−1, respectively. Comparedwith the temporary sink, the net sink of CO2 for the Bei Jiangwas approximately 23.18×103 mol km−2 a−1 of CO2 sinkingin the global carbon cycling. It was about 3 % of the tempo-rary CO2 sink. In addition, the CO2 net sink of each subbasinwas also different and showed large spatial variations due toheterogeneity of geology and human activities. The geologyshowed weak correlation with the CO2 net sink (Fig. 12a),while the [SO2−4 ]SCW and [SO

2−4 ]SSW have weak negative

correlation with the CO2 net sink (Fig. 12b). This provedthat human activities (sulfur acid deposition and AMD) de-creased the CO2 net sink and even made chemical weatheringa CO2 source to the atmosphere.

6 Conclusions

This study revealed the temporary and net sinks of atmo-spheric CO2 due to chemical weathering in a subtropicalhyperactive catchment with mixing carbonate and silicatelithology under the stress of chemical weathering induced byanthropogenic sulfuric acid agent. During the sampling pe-riod, the pH values ranged from 7.5 to 8.5 and TDS variedfrom 73.8 to 230.2 mg L−1. Ca2+ and HCO−3 were the dom-inant cation and anion. Water chemical patterns and PCAshowed that carbonate and silicate weathering were the most

important processes controlling the local hydrochemistry. Onaverage, carbonate and silicate weathering contributed ap-proximately 50.06 % and 25.71 % of the total cationic loads,respectively.

The averages of carbonate and silicate weathering rate inthe Bei Jiang basin were 61.15 and 25.31 t km−2 a−1, respec-tively. The high rate was comparable to other rivers locatedin the hyperactive zone between the latitude 0 and 30◦. Thelithology, runoff, and geomorphology had significant influ-ences on the chemical weathering rate. (1) Due to the differ-ence between kinetics of carbonate and silicate dissolutionprocesses, the proportion of carbonate outcrops had signif-icant positive correlation with the chemical weathering rateand confirmed that carbonate outcrop ratios were the sen-sitive factor controlling the chemical weathering rates, andthe rapid kinetics of carbonate dissolution played an impor-tant role in weathering rates. (2) Runoff mainly controlledthe season variations, and the dilution effect was weak inthe study area. Due to the compensation effect of chemicalweathering, a significant positive linear relationship was de-tected between Q and TWR, CWR, and SWR. (3) The ge-omorphology factors such as slope and HI had a nonlinearcorrelation with chemical weathering rate and showed a sig-nificant scale effect, which revealed the complexity in chem-ical weathering processes.

DIC apportionment showed that CCW was the domi-nant origin of DIC (35 %–87 %) and that SCW (3 %–15 %)and CSW (7 %–59 %) were non-negligible weathering pro-cesses. The CCRTotal was 823.41× 103 mol km−2 a−1, rel-atively high CCR due to a high chemical weathering rate.In addition, the CCRCCW and CCRCSW were 536.59× 103

(65 %) and 286.82× 103 (35 %) mol km−2 a−1, respectively.



Compared with the temporary sink, the net sink of CO2 forthe Bei Jiang was approximately 23.18× 103 mol km−2 a−1

of CO2 sinking in global carbon cycling. It was about 2.82 %of the temporary CO2 sink. Human activities such as sulfuracid deposition and AMD have significantly altered the CO2sinks.

Data availability. The data in this study have been presented in thetables of the article and can also be requested from the correspond-ing author.

Supplement. The supplement related to this article is available on-line at: https://doi.org/10.5194/bg-17-3875-2020-supplement.

Author contributions. YC and CT designed the study, carried outthe fieldwork, analyzed the results, and drafted the manuscript. YXand SG participated in the field sampling and laboratory analysis.YP reviewed and edited the original draft of the manuscript. Allauthors read and approved the final manuscript.

Competing interests. The authors declare that they have no conflictof interest.

Acknowledgements. This research work was financially supportedby the General Program of the National Natural Science Foun-dation of China (no. 41877470) and the Natural Science Foun-dation of Guangdong Province, China (nos. 2017A030313231,2017A030313229).

Financial support. This research has been supported by the Gen-eral Program of the National Natural Science Foundation of China(grant no. 41877470) and the Natural Science Foundation ofGuangdong Province, China (grant nos. 2017A030313231 and2017A030313229).

Review statement. This paper was edited by Nobuhito Ohte and re-viewed by two anonymous referees.

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AbstractIntroductionStudy areaMaterials and methodsSampling procedure and laboratory analysisCalculation procedureChemical weathering ratesDIC apportionmentsCO2 consumption rate and CO2 net sink

Spatial and statistical analysis

ResultsChemical compositionsSeasonal and spatial variations

DiscussionChemical weathering rates and the controlling factorsChemical weathering ratesFactors affecting chemical weathering

Temporary and net sink of atmospheric CO2Sulfate origin and DIC apportionmentTemporary and net CO2 sink

ConclusionsData availabilitySupplementAuthor contributionsCompeting interestsAcknowledgementsFinancial supportReview statementReferences

temporary and net sinks of atmospheric co due to chemical … · 2020. 7. 31. · chemical...

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